�ݺ�ߣ

Dr jadidi fluent-basic-m07

Jun 17, 20200 likes99 views

Mohammad Jadidi

Goal: In these power point presentations, the basics of applied CFD simulation in the industry using powerful ANSYS-FLUENT software is presented.

ANSYS Fluent (basic)
Module 07
Instructor:
Dr. Mohammad Jadidi
(Ph.D. in Mechanical Engineering)

Instructor: Dr. Mohammad Jadidi

Instructor: Dr. Mohammad Jadidi

Instructor: Dr. Mohammad Jadidi

Instructor: Dr. Mohammad Jadidi

Instructor: Dr. Mohammad Jadidi

Instructor: Dr. Mohammad Jadidi

Instructor: Dr. Mohammad Jadidi

Instructor: Dr. Mohammad Jadidi

Instructor: Dr. Mohammad Jadidi

Instructor: Dr. Mohammad Jadidi

Instructor: Dr. Mohammad Jadidi

Instructor: Dr. Mohammad Jadidi

Instructor: Dr. Mohammad Jadidi

Instructor: Dr. Mohammad Jadidi

Instructor: Dr. Mohammad Jadidi

Instructor: Dr. Mohammad Jadidi

Instructor: Dr. Mohammad Jadidi

Instructor: Dr. Mohammad Jadidi

Instructor: Dr. Mohammad Jadidi

Instructor: Dr. Mohammad Jadidi

Instructor: Dr. Mohammad Jadidi

Instructor: Dr. Mohammad Jadidi

Instructor: Dr. Mohammad Jadidi

Instructor: Dr. Mohammad Jadidi

Instructor: Dr. Mohammad Jadidi

Instructor: Dr. Mohammad Jadidi

Instructor: Dr. Mohammad Jadidi

Instructor: Dr. Mohammad Jadidi

Instructor: Dr. Mohammad Jadidi

Instructor: Dr. Mohammad Jadidi

Instructor: Dr. Mohammad Jadidi

Instructor: Dr. Mohammad Jadidi

Instructor: Dr. Mohammad Jadidi

Instructor: Dr. Mohammad Jadidi

Instructor: Dr. Mohammad Jadidi

Instructor: Dr. Mohammad Jadidi

Instructor: Dr. Mohammad Jadidi

Instructor: Dr. Mohammad Jadidi

Instructor: Dr. Mohammad Jadidi

Instructor: Dr. Mohammad Jadidi

Instructor: Dr. Mohammad Jadidi

Instructor: Dr. Mohammad Jadidi

Instructor: Dr. Mohammad Jadidi

Instructor: Dr. Mohammad Jadidi

Thanks
Jadidi.cfd@gmail.com
Dr. Mohammad Jadidi
(Postdoctoral in Mechanical Engineering)
End of Module 07 Next part:
ANSYS Fluent (basic)

Recommended

Dr jadidi fluent-basic-m08

Dr jadidi fluent-basic-m08

Dr jadidi fluent-basic-m08Mohammad Jadidi

��

Dr jadidi fluent-basic-m03

Dr jadidi fluent-basic-m03

Dr jadidi fluent-basic-m03Mohammad Jadidi

��

Dr jadidi fluent-basic-m09

Dr jadidi fluent-basic-m09

Dr jadidi fluent-basic-m09Mohammad Jadidi

��

Dr jadidi fluent-basic-m05

Dr jadidi fluent-basic-m05

Dr jadidi fluent-basic-m05Mohammad Jadidi

��

Dr jadidi fluent-basic-m04

Dr jadidi fluent-basic-m04

Dr jadidi fluent-basic-m04Mohammad Jadidi

��

Dr jadidi fluent-basic-m02

Dr jadidi fluent-basic-m02

Dr jadidi fluent-basic-m02Mohammad Jadidi

��

Dr jadidi fluent-basic-m06

Dr jadidi fluent-basic-m06

Dr jadidi fluent-basic-m06Mohammad Jadidi

��

Dr jadidi fluent-basic-m01

Dr jadidi fluent-basic-m01

Dr jadidi fluent-basic-m01Mohammad Jadidi

��

Turbulence near the wall.pdf

Turbulence near the wall.pdf

Turbulence near the wall.pdfMohammad Jadidi

��

The document discusses turbulence near walls and different approaches to modeling it in computational fluid dynamics (CFD). It explains that the boundary layer can be divided into different zones, and CFD requires different considerations depending on whether the viscous sub-layer is solved, the log-law layer is modeled, or the whole boundary layer is solved. It also discusses the use of non-dimensional variables to characterize the boundary layer and describes different near-wall treatments in CFD, including resolving the boundary layer with fine meshes or using wall functions with coarser meshes.

Introduction to CFD- Chapter 1

Introduction to CFD- Chapter 1

Introduction to CFD- Chapter 1Mohammad Jadidi

��

Dr jadidi fluent-basic-m010-homework

Dr jadidi fluent-basic-m010-homework

Dr jadidi fluent-basic-m010-homeworkMohammad Jadidi

��

Dr jadidi fluent-basic-m01-b

Dr jadidi fluent-basic-m01-b

Dr jadidi fluent-basic-m01-bMohammad Jadidi

��

04 reactive flows - eddy disipation model

04 reactive flows - eddy disipation model

04 reactive flows - eddy disipation modelMohammad Jadidi

��

The document discusses reactive flow modeling using the eddy dissipation model (EDM) in ANSYS Fluent. EDM solves conservation equations for chemical species by predicting local mass fractions through a convection-diffusion equation. Reaction rates are assumed to be controlled by turbulence, ignoring chemical timescales. EDM gives the smaller of two expressions to calculate reaction rates, with the chemical reaction rate governed by the large eddy mixing timescale. EDM is computationally cheap but works best for one-two step global reactions, as it cannot capture detailed chemistry effects.

01 reactive flows - governing equations favre averaging

01 reactive flows - governing equations favre averaging

01 reactive flows - governing equations favre averaging Mohammad Jadidi

��

This document discusses reactive flow modeling in combustion chambers. It covers the equations governing reacting flows, including conservation equations for mass, momentum, molecular species, and energy. It also discusses the equation of state and turbulence transport. The document then covers statistical descriptions of turbulent flows using Reynolds decomposition and Favre averaging. Favre averaging is preferred for reacting flows with variable density as it leads to simpler expressions in the transport equations for continuity, momentum, species, and energy compared to Reynolds averaging. Various terms that arise in the averaged equations require turbulence modeling approaches.

00 reactive flows - governing equations

00 reactive flows - governing equations

00 reactive flows - governing equationsMohammad Jadidi

��

The document discusses the governing equations for reacting flows, including conservation of mass, momentum, molecular species, and energy. It outlines the continuity, momentum, species transport, and energy equations. The species transport equation accounts for convection, diffusion, and chemical reaction sources. The energy equation considers changes in enthalpy due to convection, diffusion, pressure work, and radiation. Simplifications are discussed under certain assumptions, such as a single diffusion coefficient and negligible pressure work/radiation terms, in which case enthalpy behaves as a passive scalar. Other relationships presented include the equation of state and definitions of specific heat capacity and density.

01 reactive flows - finite-rate formulation for reaction modeling

01 reactive flows - finite-rate formulation for reaction modeling

01 reactive flows - finite-rate formulation for reaction modelingMohammad Jadidi

��

This document discusses equations governing reacting flows as modeled in ANSYS Fluent. It describes how Fluent solves conservation equations for species mass fractions using a convection-diffusion equation, where the chemical source term Ri accounts for reaction rates. Finite-rate kinetics and turbulence-chemistry interaction models are discussed for determining Ri, including the eddy dissipation model. The Arrhenius equation is also presented for calculating forward reaction rate constants based on pre-exponential factors, temperature exponents, and activation energies specified in the kinetic mechanism.

00 reactive flows - species transport

00 reactive flows - species transport

00 reactive flows - species transportMohammad Jadidi

��

01 multiphase flows- fundamental definitions

01 multiphase flows- fundamental definitions

01 multiphase flows- fundamental definitionsMohammad Jadidi

��

00 multiphase flows - intorduction

00 multiphase flows - intorduction

00 multiphase flows - intorductionMohammad Jadidi

��

The document discusses different types of multiphase flows. It defines multiphase flow as any fluid system with two or more distinct phases flowing simultaneously in mixture. Multiphase flows are classified into four main categories: gas-liquid flows, gas-solid flows, liquid-solid flows, and three-phase flows. Each category contains different flow regimes depending on factors like particle size and flow rates. Flow maps are used to characterize different flow patterns that can occur for a given system.

RANS-LES-DNSMohammad Jadidi

��

1Mohammad Jadidi

��

jadiditurbulencemodeling

jadiditurbulencemodeling

jadiditurbulencemodelingMohammad Jadidi

��

This document discusses turbulence modeling in computational fluid dynamics (CFD). It contains three main points: 1. Turbulence models used in CFD simulations like RANS and LES are introduced. Important turbulence concepts such as eddies, length scales, and the energy cascade are explained. 2. Reynolds-averaged Navier-Stokes (RANS) equations are presented along with Reynolds stress tensor and turbulent heat flux terms. Common RANS turbulence models and their governing equations are outlined. 3. Large eddy simulation (LES) is described as an alternative to RANS. Filtering operations in LES to separate large and small scales are discussed. Root-mean-square velocities are presented as a

wallfunctionMohammad Jadidi

��

LES_jadidi#2Mohammad Jadidi

��

CFD-jadidi#2Mohammad Jadidi

��

1Mohammad Jadidi

��

Presentation 4Mohammad Jadidi

��

Presentation3Mohammad Jadidi

��

Air pollution is contamination of the indoor or outdoor environment by any ch...

Air pollution is contamination of the indoor or outdoor environment by any ch...

Air pollution is contamination of the indoor or outdoor environment by any ch...dhanashree78

��

Air pollution is contamination of the indoor or outdoor environment by any chemical, physical or biological agent that modifies the natural characteristics of the atmosphere. Household combustion devices, motor vehicles, industrial facilities and forest fires are common sources of air pollution. Pollutants of major public health concern include particulate matter, carbon monoxide, ozone, nitrogen dioxide and sulfur dioxide. Outdoor and indoor air pollution cause respiratory and other diseases and are important sources of morbidity and mortality. WHO data show that almost all of the global population (99%) breathe air that exceeds WHO guideline limits and contains high levels of pollutants, with low- and middle-income countries suffering from the highest exposures. Air quality is closely linked to the earth’s climate and ecosystems globally. Many of the drivers of air pollution (i.e. combustion of fossil fuels) are also sources of greenhouse gas emissions. Policies to reduce air pollution, therefore, offer a win-win strategy for both climate and health, lowering the burden of disease attributable to air pollution, as well as contributing to the near- and long-term mitigation of climate change.

Cloud Computing concepts and technologies

Cloud Computing concepts and technologies

Cloud Computing concepts and technologiesssuser4c9444

��

More Related Content

More from Mohammad Jadidi (20)

Turbulence near the wall.pdf

Turbulence near the wall.pdf

Turbulence near the wall.pdfMohammad Jadidi

��

The document discusses turbulence near walls and different approaches to modeling it in computational fluid dynamics (CFD). It explains that the boundary layer can be divided into different zones, and CFD requires different considerations depending on whether the viscous sub-layer is solved, the log-law layer is modeled, or the whole boundary layer is solved. It also discusses the use of non-dimensional variables to characterize the boundary layer and describes different near-wall treatments in CFD, including resolving the boundary layer with fine meshes or using wall functions with coarser meshes.

Introduction to CFD- Chapter 1

Introduction to CFD- Chapter 1

Introduction to CFD- Chapter 1Mohammad Jadidi

��

Dr jadidi fluent-basic-m010-homework

Dr jadidi fluent-basic-m010-homework

Dr jadidi fluent-basic-m010-homeworkMohammad Jadidi

��

Dr jadidi fluent-basic-m01-b

Dr jadidi fluent-basic-m01-b

Dr jadidi fluent-basic-m01-bMohammad Jadidi

��

04 reactive flows - eddy disipation model

04 reactive flows - eddy disipation model

04 reactive flows - eddy disipation modelMohammad Jadidi

��

The document discusses reactive flow modeling using the eddy dissipation model (EDM) in ANSYS Fluent. EDM solves conservation equations for chemical species by predicting local mass fractions through a convection-diffusion equation. Reaction rates are assumed to be controlled by turbulence, ignoring chemical timescales. EDM gives the smaller of two expressions to calculate reaction rates, with the chemical reaction rate governed by the large eddy mixing timescale. EDM is computationally cheap but works best for one-two step global reactions, as it cannot capture detailed chemistry effects.

01 reactive flows - governing equations favre averaging

01 reactive flows - governing equations favre averaging

01 reactive flows - governing equations favre averaging Mohammad Jadidi

��

This document discusses reactive flow modeling in combustion chambers. It covers the equations governing reacting flows, including conservation equations for mass, momentum, molecular species, and energy. It also discusses the equation of state and turbulence transport. The document then covers statistical descriptions of turbulent flows using Reynolds decomposition and Favre averaging. Favre averaging is preferred for reacting flows with variable density as it leads to simpler expressions in the transport equations for continuity, momentum, species, and energy compared to Reynolds averaging. Various terms that arise in the averaged equations require turbulence modeling approaches.

00 reactive flows - governing equations

00 reactive flows - governing equations

00 reactive flows - governing equationsMohammad Jadidi

��

The document discusses the governing equations for reacting flows, including conservation of mass, momentum, molecular species, and energy. It outlines the continuity, momentum, species transport, and energy equations. The species transport equation accounts for convection, diffusion, and chemical reaction sources. The energy equation considers changes in enthalpy due to convection, diffusion, pressure work, and radiation. Simplifications are discussed under certain assumptions, such as a single diffusion coefficient and negligible pressure work/radiation terms, in which case enthalpy behaves as a passive scalar. Other relationships presented include the equation of state and definitions of specific heat capacity and density.

01 reactive flows - finite-rate formulation for reaction modeling

01 reactive flows - finite-rate formulation for reaction modeling

01 reactive flows - finite-rate formulation for reaction modelingMohammad Jadidi

��

This document discusses equations governing reacting flows as modeled in ANSYS Fluent. It describes how Fluent solves conservation equations for species mass fractions using a convection-diffusion equation, where the chemical source term Ri accounts for reaction rates. Finite-rate kinetics and turbulence-chemistry interaction models are discussed for determining Ri, including the eddy dissipation model. The Arrhenius equation is also presented for calculating forward reaction rate constants based on pre-exponential factors, temperature exponents, and activation energies specified in the kinetic mechanism.

00 reactive flows - species transport

00 reactive flows - species transport

00 reactive flows - species transportMohammad Jadidi

��

01 multiphase flows- fundamental definitions

01 multiphase flows- fundamental definitions

01 multiphase flows- fundamental definitionsMohammad Jadidi

��

00 multiphase flows - intorduction

00 multiphase flows - intorduction

00 multiphase flows - intorductionMohammad Jadidi

��

The document discusses different types of multiphase flows. It defines multiphase flow as any fluid system with two or more distinct phases flowing simultaneously in mixture. Multiphase flows are classified into four main categories: gas-liquid flows, gas-solid flows, liquid-solid flows, and three-phase flows. Each category contains different flow regimes depending on factors like particle size and flow rates. Flow maps are used to characterize different flow patterns that can occur for a given system.

RANS-LES-DNSMohammad Jadidi

��

1Mohammad Jadidi

��

jadiditurbulencemodeling

jadiditurbulencemodeling

jadiditurbulencemodelingMohammad Jadidi

��

This document discusses turbulence modeling in computational fluid dynamics (CFD). It contains three main points: 1. Turbulence models used in CFD simulations like RANS and LES are introduced. Important turbulence concepts such as eddies, length scales, and the energy cascade are explained. 2. Reynolds-averaged Navier-Stokes (RANS) equations are presented along with Reynolds stress tensor and turbulent heat flux terms. Common RANS turbulence models and their governing equations are outlined. 3. Large eddy simulation (LES) is described as an alternative to RANS. Filtering operations in LES to separate large and small scales are discussed. Root-mean-square velocities are presented as a

wallfunctionMohammad Jadidi

��

LES_jadidi#2Mohammad Jadidi

��

CFD-jadidi#2Mohammad Jadidi

��

1Mohammad Jadidi

��

Presentation 4Mohammad Jadidi

��

Presentation3Mohammad Jadidi

��

Turbulence near the wall.pdf

Turbulence near the wall.pdf

Turbulence near the wall.pdfMohammad Jadidi

��

Introduction to CFD- Chapter 1

Introduction to CFD- Chapter 1

Introduction to CFD- Chapter 1Mohammad Jadidi

��

Dr jadidi fluent-basic-m010-homework

Dr jadidi fluent-basic-m010-homework

Dr jadidi fluent-basic-m010-homeworkMohammad Jadidi

��

Dr jadidi fluent-basic-m01-b

Dr jadidi fluent-basic-m01-b

Dr jadidi fluent-basic-m01-bMohammad Jadidi

��

04 reactive flows - eddy disipation model

04 reactive flows - eddy disipation model

04 reactive flows - eddy disipation modelMohammad Jadidi

��

01 reactive flows - governing equations favre averaging

01 reactive flows - governing equations favre averaging

01 reactive flows - governing equations favre averaging Mohammad Jadidi

��

00 reactive flows - governing equations

00 reactive flows - governing equations

00 reactive flows - governing equationsMohammad Jadidi

��

01 reactive flows - finite-rate formulation for reaction modeling

01 reactive flows - finite-rate formulation for reaction modeling

01 reactive flows - finite-rate formulation for reaction modelingMohammad Jadidi

��

00 reactive flows - species transport

00 reactive flows - species transport

00 reactive flows - species transportMohammad Jadidi

��

01 multiphase flows- fundamental definitions

01 multiphase flows- fundamental definitions

01 multiphase flows- fundamental definitionsMohammad Jadidi

��

00 multiphase flows - intorduction

00 multiphase flows - intorduction

00 multiphase flows - intorductionMohammad Jadidi

��

RANS-LES-DNSMohammad Jadidi

��

1Mohammad Jadidi

��

jadiditurbulencemodeling

jadiditurbulencemodeling

jadiditurbulencemodelingMohammad Jadidi

��

wallfunctionMohammad Jadidi

��

LES_jadidi#2Mohammad Jadidi

��

CFD-jadidi#2Mohammad Jadidi

��

1Mohammad Jadidi

��

Presentation 4Mohammad Jadidi

��

Presentation3Mohammad Jadidi

��

Recently uploaded (20)

Air pollution is contamination of the indoor or outdoor environment by any ch...

Air pollution is contamination of the indoor or outdoor environment by any ch...

Air pollution is contamination of the indoor or outdoor environment by any ch...dhanashree78

��

Air pollution is contamination of the indoor or outdoor environment by any chemical, physical or biological agent that modifies the natural characteristics of the atmosphere. Household combustion devices, motor vehicles, industrial facilities and forest fires are common sources of air pollution. Pollutants of major public health concern include particulate matter, carbon monoxide, ozone, nitrogen dioxide and sulfur dioxide. Outdoor and indoor air pollution cause respiratory and other diseases and are important sources of morbidity and mortality. WHO data show that almost all of the global population (99%) breathe air that exceeds WHO guideline limits and contains high levels of pollutants, with low- and middle-income countries suffering from the highest exposures. Air quality is closely linked to the earth’s climate and ecosystems globally. Many of the drivers of air pollution (i.e. combustion of fossil fuels) are also sources of greenhouse gas emissions. Policies to reduce air pollution, therefore, offer a win-win strategy for both climate and health, lowering the burden of disease attributable to air pollution, as well as contributing to the near- and long-term mitigation of climate change.

Cloud Computing concepts and technologies

Cloud Computing concepts and technologies

Cloud Computing concepts and technologiesssuser4c9444

��

Best KNow Hydrogen Fuel Production in the World The cost in USD kwh for H2

Best KNow Hydrogen Fuel Production in the World The cost in USD kwh for H2

Best KNow Hydrogen Fuel Production in the World The cost in USD kwh for H2Daniel Donatelli

��

The cost in USD/kwh for H2 Daniel Donatelli Secure Supplies Group Index • Introduction - Page 3 • The Need for Hydrogen Fueling - Page 5 • Pure H2 Fueling Technology - Page 7 • Blend Gas Fueling: A Transition Strategy - Page 10 • Performance Metrics: H2 vs. Fossil Fuels - Page 12 • Cost Analysis and Economic Viability - Page 15 • Innovations Driving Leadership - Page 18 • Laminar Flame Speed Adjustment • Heat Management Systems • The Donatelli Cycle • Non-Carnot Cycle Applications • Case Studies and Real-World Applications - Page 22 • Conclusion: Secure Supplies’ Leadership in Hydrogen Fueling - Page 27

How to Make an RFID Door Lock System using Arduino

How to Make an RFID Door Lock System using Arduino

How to Make an RFID Door Lock System using ArduinoCircuitDigest

��

GROUP-3-GRID-CODE-AND-DISTRIBUTION-CODE.pptx

GROUP-3-GRID-CODE-AND-DISTRIBUTION-CODE.pptx

GROUP-3-GRID-CODE-AND-DISTRIBUTION-CODE.pptxmeneememoo

��

Cyber Security_ Protecting the Digital World.pptx

Cyber Security_ Protecting the Digital World.pptx

Cyber Security_ Protecting the Digital World.pptxHarshith A S

��

GM Meeting 070225 TO 130225 for 2024.pptx

GM Meeting 070225 TO 130225 for 2024.pptx

GM Meeting 070225 TO 130225 for 2024.pptxcrdslalcomumbai

��

Mathematics behind machine learning INT255 INT255__Unit 3__PPT-1.pptx

Mathematics behind machine learning INT255 INT255__Unit 3__PPT-1.pptx

Mathematics behind machine learning INT255 INT255__Unit 3__PPT-1.pptxppkmurthy2006

��

Engineering at Lovely Professional University (LPU).pdf

Engineering at Lovely Professional University (LPU).pdf

Engineering at Lovely Professional University (LPU).pdfSona

��

Frankfurt University of Applied Science urkunde

Frankfurt University of Applied Science urkunde

Frankfurt University of Applied Science urkundeLisa Emerson

��

Lessons learned when managing MySQL in the Cloud

Lessons learned when managing MySQL in the Cloud

Lessons learned when managing MySQL in the CloudIgor Donchovski

��

Managing MySQL in the cloud introduces a new set of challenges compared to traditional on-premises setups, from ensuring optimal performance to handling unexpected outages. In this article, we delve into covering topics such as performance tuning, cost-effective scalability, and maintaining high availability. We also explore the importance of monitoring, automation, and best practices for disaster recovery to minimize downtime.

Mathematics_behind_machine_learning_INT255.pptx

Mathematics_behind_machine_learning_INT255.pptx

Mathematics_behind_machine_learning_INT255.pptxppkmurthy2006

��

autonomous vehicle project for engineering.pdf

autonomous vehicle project for engineering.pdf

autonomous vehicle project for engineering.pdfJyotiLohar6

��

Multi objective genetic approach with Ranking

Multi objective genetic approach with Ranking

Multi objective genetic approach with Rankingnamisha18

��

Optimization of Cumulative Energy, Exergy Consumption and Environmental Life ...

Optimization of Cumulative Energy, Exergy Consumption and Environmental Life ...

Optimization of Cumulative Energy, Exergy Consumption and Environmental Life ...J. Agricultural Machinery

��

Optimal use of resources, including energy, is one of the most important principles in modern and sustainable agricultural systems. Exergy analysis and life cycle assessment were used to study the efficient use of inputs, energy consumption reduction, and various environmental effects in the corn production system in Lorestan province, Iran. The required data were collected from farmers in Lorestan province using random sampling. The Cobb-Douglas equation and data envelopment analysis were utilized for modeling and optimizing cumulative energy and exergy consumption (CEnC and CExC) and devising strategies to mitigate the environmental impacts of corn production. The Cobb-Douglas equation results revealed that electricity, diesel fuel, and N-fertilizer were the major contributors to CExC in the corn production system. According to the Data Envelopment Analysis (DEA) results, the average efficiency of all farms in terms of CExC was 94.7% in the CCR model and 97.8% in the BCC model. Furthermore, the results indicated that there was excessive consumption of inputs, particularly potassium and phosphate fertilizers. By adopting more suitable methods based on DEA of efficient farmers, it was possible to save 6.47, 10.42, 7.40, 13.32, 31.29, 3.25, and 6.78% in the exergy consumption of diesel fuel, electricity, machinery, chemical fertilizers, biocides, seeds, and irrigation, respectively.

google_developer_group_ramdeobaba_university_EXPLORE_PPT

google_developer_group_ramdeobaba_university_EXPLORE_PPT

google_developer_group_ramdeobaba_university_EXPLORE_PPTJayeshShete1

��

EXPLORE 6 EXCITING DOMAINS: 1. Machine Learning: Discover the world of AI and ML! 2. App Development: Build innovative mobile apps! 3. Competitive Programming: Enhance your coding skills! 4. Web Development: Create stunning web applications! 5. Blockchain: Uncover the power of decentralized tech! 6. Cloud Computing: Explore the world of cloud infrastructure! Join us to unravel the unexplored, network with like-minded individuals, and dive into the world of tech!

US Patented ReGenX Generator, ReGen-X Quatum Motor EV Regenerative Accelerati...

US Patented ReGenX Generator, ReGen-X Quatum Motor EV Regenerative Accelerati...

US Patented ReGenX Generator, ReGen-X Quatum Motor EV Regenerative Accelerati...Thane Heins NOBEL PRIZE WINNING ENERGY RESEARCHER

��

Preface: The ReGenX Generator innovation operates with a US Patented Frequency Dependent Load Current Delay which delays the creation and storage of created Electromagnetic Field Energy around the exterior of the generator coil. The result is the created and Time Delayed Electromagnetic Field Energy performs any magnitude of Positive Electro-Mechanical Work at infinite efficiency on the generator's Rotating Magnetic Field, increasing its Kinetic Energy and increasing the Kinetic Energy of an EV or ICE Vehicle to any magnitude without requiring any Externally Supplied Input Energy. In Electricity Generation applications the ReGenX Generator innovation now allows all electricity to be generated at infinite efficiency requiring zero Input Energy, zero Input Energy Cost, while producing zero Greenhouse Gas Emissions, zero Air Pollution and zero Nuclear Waste during the Electricity Generation Phase. In Electric Motor operation the ReGen-X Quantum Motor now allows any magnitude of Work to be performed with zero Electric Input Energy. Demonstration Protocol: The demonstration protocol involves three prototypes; 1. Protytpe #1, demonstrates the ReGenX Generator's Load Current Time Delay when compared to the instantaneous Load Current Sine Wave for a Conventional Generator Coil. 2. In the Conventional Faraday Generator operation the created Electromagnetic Field Energy performs Negative Work at infinite efficiency and it reduces the Kinetic Energy of the system. 3. The Magnitude of the Negative Work / System Kinetic Energy Reduction (in Joules) is equal to the Magnitude of the created Electromagnetic Field Energy (also in Joules). 4. When the Conventional Faraday Generator is placed On-Load, Negative Work is performed and the speed of the system decreases according to Lenz's Law of Induction. 5. In order to maintain the System Speed and the Electric Power magnitude to the Loads, additional Input Power must be supplied to the Prime Mover and additional Mechanical Input Power must be supplied to the Generator's Drive Shaft. 6. For example, if 100 Watts of Electric Power is delivered to the Load by the Faraday Generator, an additional >100 Watts of Mechanical Input Power must be supplied to the Generator's Drive Shaft by the Prime Mover. 7. If 1 MW of Electric Power is delivered to the Load by the Faraday Generator, an additional >1 MW Watts of Mechanical Input Power must be supplied to the Generator's Drive Shaft by the Prime Mover. 8. Generally speaking the ratio is 2 Watts of Mechanical Input Power to every 1 Watt of Electric Output Power generated. 9. The increase in Drive Shaft Mechanical Input Power is provided by the Prime Mover and the Input Energy Source which powers the Prime Mover. 10. In the Heins ReGenX Generator operation the created and Time Delayed Electromagnetic Field Energy performs Positive Work at infinite efficiency and it increases the Kinetic Energy of the system.

decarbonization steel industry rev1.pptx

decarbonization steel industry rev1.pptx

decarbonization steel industry rev1.pptxgonzalezolabarriaped

��

Turbocor Product and Technology Review.pdf

Turbocor Product and Technology Review.pdf

Turbocor Product and Technology Review.pdfTotok Sulistiyanto

��

Lectureof nano 1588236675-biosensors (1).ppt

Lectureof nano 1588236675-biosensors (1).ppt

Lectureof nano 1588236675-biosensors (1).pptSherifElGohary7

��

Air pollution is contamination of the indoor or outdoor environment by any ch...

Air pollution is contamination of the indoor or outdoor environment by any ch...

Air pollution is contamination of the indoor or outdoor environment by any ch...dhanashree78

��

Cloud Computing concepts and technologies

Cloud Computing concepts and technologies

Cloud Computing concepts and technologiesssuser4c9444

��

Best KNow Hydrogen Fuel Production in the World The cost in USD kwh for H2

Best KNow Hydrogen Fuel Production in the World The cost in USD kwh for H2

Best KNow Hydrogen Fuel Production in the World The cost in USD kwh for H2Daniel Donatelli

��

How to Make an RFID Door Lock System using Arduino

How to Make an RFID Door Lock System using Arduino

How to Make an RFID Door Lock System using ArduinoCircuitDigest

��

GROUP-3-GRID-CODE-AND-DISTRIBUTION-CODE.pptx

GROUP-3-GRID-CODE-AND-DISTRIBUTION-CODE.pptx

GROUP-3-GRID-CODE-AND-DISTRIBUTION-CODE.pptxmeneememoo

��

Cyber Security_ Protecting the Digital World.pptx

Cyber Security_ Protecting the Digital World.pptx

Cyber Security_ Protecting the Digital World.pptxHarshith A S

��

GM Meeting 070225 TO 130225 for 2024.pptx

GM Meeting 070225 TO 130225 for 2024.pptx

GM Meeting 070225 TO 130225 for 2024.pptxcrdslalcomumbai

��

Mathematics behind machine learning INT255 INT255__Unit 3__PPT-1.pptx

Mathematics behind machine learning INT255 INT255__Unit 3__PPT-1.pptx

Mathematics behind machine learning INT255 INT255__Unit 3__PPT-1.pptxppkmurthy2006

��

Engineering at Lovely Professional University (LPU).pdf

Engineering at Lovely Professional University (LPU).pdf

Engineering at Lovely Professional University (LPU).pdfSona

��

Frankfurt University of Applied Science urkunde

Frankfurt University of Applied Science urkunde

Frankfurt University of Applied Science urkundeLisa Emerson

��

Lessons learned when managing MySQL in the Cloud

Lessons learned when managing MySQL in the Cloud

Lessons learned when managing MySQL in the CloudIgor Donchovski

��

Mathematics_behind_machine_learning_INT255.pptx

Mathematics_behind_machine_learning_INT255.pptx

Mathematics_behind_machine_learning_INT255.pptxppkmurthy2006

��

autonomous vehicle project for engineering.pdf

autonomous vehicle project for engineering.pdf

autonomous vehicle project for engineering.pdfJyotiLohar6

��

Multi objective genetic approach with Ranking

Multi objective genetic approach with Ranking

Multi objective genetic approach with Rankingnamisha18

��

Optimization of Cumulative Energy, Exergy Consumption and Environmental Life ...

Optimization of Cumulative Energy, Exergy Consumption and Environmental Life ...

Optimization of Cumulative Energy, Exergy Consumption and Environmental Life ...J. Agricultural Machinery

��

google_developer_group_ramdeobaba_university_EXPLORE_PPT

google_developer_group_ramdeobaba_university_EXPLORE_PPT

google_developer_group_ramdeobaba_university_EXPLORE_PPTJayeshShete1

��

US Patented ReGenX Generator, ReGen-X Quatum Motor EV Regenerative Accelerati...

US Patented ReGenX Generator, ReGen-X Quatum Motor EV Regenerative Accelerati...

US Patented ReGenX Generator, ReGen-X Quatum Motor EV Regenerative Accelerati...Thane Heins NOBEL PRIZE WINNING ENERGY RESEARCHER

��

decarbonization steel industry rev1.pptx

decarbonization steel industry rev1.pptx

decarbonization steel industry rev1.pptxgonzalezolabarriaped

��

Turbocor Product and Technology Review.pdf

Turbocor Product and Technology Review.pdf

Turbocor Product and Technology Review.pdfTotok Sulistiyanto

��

Lectureof nano 1588236675-biosensors (1).ppt

Lectureof nano 1588236675-biosensors (1).ppt

Lectureof nano 1588236675-biosensors (1).pptSherifElGohary7

��

Dr jadidi fluent-basic-m07

1. ANSYS Fluent (basic) Module 07 Instructor: Dr. Mohammad Jadidi (Ph.D. in Mechanical Engineering)

2. Instructor: Dr. Mohammad Jadidi

3. Instructor: Dr. Mohammad Jadidi

4. Instructor: Dr. Mohammad Jadidi

5. Instructor: Dr. Mohammad Jadidi

6. Instructor: Dr. Mohammad Jadidi

7. Instructor: Dr. Mohammad Jadidi

8. Instructor: Dr. Mohammad Jadidi

9. Instructor: Dr. Mohammad Jadidi

10. Instructor: Dr. Mohammad Jadidi

11. Instructor: Dr. Mohammad Jadidi

12. Instructor: Dr. Mohammad Jadidi

13. Instructor: Dr. Mohammad Jadidi

14. Instructor: Dr. Mohammad Jadidi

15. Instructor: Dr. Mohammad Jadidi

16. Instructor: Dr. Mohammad Jadidi

17. Instructor: Dr. Mohammad Jadidi

18. Instructor: Dr. Mohammad Jadidi

19. Instructor: Dr. Mohammad Jadidi

20. Instructor: Dr. Mohammad Jadidi

21. Instructor: Dr. Mohammad Jadidi

22. Instructor: Dr. Mohammad Jadidi

23. Instructor: Dr. Mohammad Jadidi

24. Instructor: Dr. Mohammad Jadidi

25. Instructor: Dr. Mohammad Jadidi

26. Instructor: Dr. Mohammad Jadidi

27. Instructor: Dr. Mohammad Jadidi

28. Instructor: Dr. Mohammad Jadidi

29. Instructor: Dr. Mohammad Jadidi

30. Instructor: Dr. Mohammad Jadidi

31. Instructor: Dr. Mohammad Jadidi

32. Instructor: Dr. Mohammad Jadidi

33. Instructor: Dr. Mohammad Jadidi

34. Instructor: Dr. Mohammad Jadidi

35. Instructor: Dr. Mohammad Jadidi

36. Instructor: Dr. Mohammad Jadidi

37. Instructor: Dr. Mohammad Jadidi

38. Instructor: Dr. Mohammad Jadidi

39. Instructor: Dr. Mohammad Jadidi

40. Instructor: Dr. Mohammad Jadidi

41. Instructor: Dr. Mohammad Jadidi

42. Instructor: Dr. Mohammad Jadidi

43. Instructor: Dr. Mohammad Jadidi

44. Instructor: Dr. Mohammad Jadidi

45. Instructor: Dr. Mohammad Jadidi

46. Thanks Jadidi.cfd@gmail.com Dr. Mohammad Jadidi (Postdoctoral in Mechanical Engineering) End of Module 07 Next part: ANSYS Fluent (basic)